ML Classification of Car Parking with Implicit Interaction on the Driver’s Smartphone - Human-Computer Interaction – INTERACT 2021
Conference Papers Year : 2021

ML Classification of Car Parking with Implicit Interaction on the Driver’s Smartphone

Abstract

On-street parking places parallel to the curb have variable lengths, depending on the size of the car that emptied the place. Thus, a Smart Parking system should publish such places only to drivers whose car is shorter than the available parking length. We developed a crowdsourced Smart Parking app, based on implicit interaction, intending to publish an available parking spot only to drivers whose car can fit the existing place. This app detects the type of parking (parallel vs angle or perpendicular) using machine learning on the driver’s smartphone and considers the length of the cars involved.
Fichier principal
Vignette du fichier
520517_1_En_21_Chapter.pdf (1.18 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04292370 , version 1 (17-11-2023)

Licence

Identifiers

Cite

Enrico Bassetti, Alessio Luciani, Emanuele Panizzi. ML Classification of Car Parking with Implicit Interaction on the Driver’s Smartphone. 18th IFIP Conference on Human-Computer Interaction (INTERACT), Aug 2021, Bari, Italy. pp.291-299, ⟨10.1007/978-3-030-85613-7_21⟩. ⟨hal-04292370⟩
29 View
31 Download

Altmetric

Share

More